Nonlinear backstepping control with adaptive modified recurrent Laguerre orthogonal polynomial NN uncertainty observer for a SynRM servo-drive system

A nonlinear backstepping control system using an adaptive modified recurrent Laguerre orthogonal polynomial neural network (NN) uncertainty observer is proposed to increase the robustness of the synchronous reluctance motor (SynRM) drive system. Firstly, the field-oriented mechanism is applied to formulate the dynamic equation of the SynRM drive system. Secondly, a nonlinear backstepping approach is proposed to control the motion of SynRM drive system. The proposed backstepping control system, the rotor position of the SynRM drive possesses the advantages of good transient control performance and robustness. Because of the existing of nonlinear time-varying uncertainties in the SynRM drive system, an adaptive modified recurrent Laguerre orthogonal polynomial NN uncertainty observer is proposed to estimate the lumped uncertainties in order to enhance robustness of the SynRM drive system. Finally, the effectiveness of the proposed control system is verified by experimental results.